";
		print_r($array);
		print "
";
		
	}
	/*-----------------------------------------------------------------------------------------------------
	Function : print_decision_tree()  
	Description: 
	------------------------------------------------------------------------------------------------------*/
	function print_decision_tree(){
		//print "Information Gain for Each Attribute
";
		print "
Starting Information Gain Values 
";
		for($i=0;$i<$this->number_attributes;$i++){
			if ($i !=0){
				print $this->attribute_titles[$i].": ".$this->info_gain[$i]."
";
			}
		}
		
		print "

Decision Tree 
";
		for($i=0;$idecision_tree);$i++){
			print $this->decision_tree[$i]."
";
		}
		
		print "

Training Data
";
		//test print the cases have been imported correctly 
		$this->print_matrix($this->cases, $this->number_cases, $this->number_attributes);
	}
	/*-----------------------------------------------------------------------------------------------------
	Function : build_decision_tree()  
	Description: 
	------------------------------------------------------------------------------------------------------*/
	function build_decision_tree(){
	
			$this->calculate_info_gain();
			//build name value associated info gain array, ie keys are attribute names
			
			$info_gain_names = array();
			for($i=1; $i<$this->number_attributes; $i++){
				$info_gain_names[$this->attribute_titles[$i]] = (int)($this->info_gain[$i]*10000);
			} 	
			
			
			//get the attribute info gains and sort them highest at index 0 etc
			$info_gain = $this->info_gain;
			asort($info_gain_names);
			//swap values with key names
			$this->info_gain_names = array_flip($info_gain_names);
			//print_r ($info_gain_names);
			$this->tree_level = '';
					
			//print_r ($this->info_gain_names);
			//print "
";
			
			//build attribute node
			$this->build_attribute_node($root=true);
			
	}//end build decision tree
	
	/*-----------------------------------------------------------------------------------------------------
	Function : build_attribute_node()  
	Description: 
	------------------------------------------------------------------------------------------------------*/
	function build_attribute_node($root=true){
			
			//if sub_info_gain you need to rebuild the info_names array
			
			//get highest info gain from info gain array and make node
			$attribute_title = array_pop($this->info_gain_names);
			//array_push($this->info_gain_names,$attribute_title);
			
			$node = "+".$this->tree_level.$attribute_title;
			
			//print $node."
";
			//save attribute node
			array_push($this->decision_tree,$node);			
			
			//make the braches (leafs)
			//get subset of target attribute values for that possible value
			$attribute_index = array_search($attribute_title, $this->attribute_titles);
			
			//get target attribute value set
			if($root)$set = $this->get_attribute($attribute_index);
			//else 
			//get the possible values
			$possible_values = $this->get_possible_values($set);	
			
			//for each possible value build possible value node
				$tree_level_pnode="--";
				for($j=0; $jbuild_branch($possible_values[$j],$set,$tree_level_pnode);
				}
			//remove attribure
			
			$tree_level_pnode.= "-";	
	}
	
	/*-----------------------------------------------------------------------------------------------------
	Function : build_branch()
	Description: builds a possible value branch for a given attribute node
	------------------------------------------------------------------------------------------------------*/
	function build_branch($possible_value,$set,$tree_level_pnode){
		
		//make possible value node
		$pnode = $tree_level_pnode.$possible_value;
		
		//get target attribute values for subset
		$sub_set = $this->target_attribute_values($set,$possible_value); 
		//calculate the entropy of the subset
		$entropy = $this->calculate_entropy($sub_set);
		
		//push the possible value node on the decision tree stack
		array_push($this->decision_tree,$pnode);
		
		while($this->info_gain_names){
		//check stop conditions	
			//entropy is not 0 or 1	start building for the next attribute	
			if($entropy != 0 || $entropy != 1 ){ 
				//calculate info gain for sub set--------------------------------------
				//needs to be implemented need to make a build subset function no time so will use original info gain 
				//$sub_info_gain = $this->calculate_info_gain($sub_set)
				$this->tree_level .= "--";
				$this->build_attribute_node($this->tree_level);
		    }
			//else you at the bottom of the tree
			
			//get sub set positive and negitive values
			else{
				$yes_no = $this->get_set_pos_neg_values($sub_set);
				$pnode .= " : ".$yes_no;
			}
		}
		//print "    ".$pnode."
";

		
	}
	
	function get_set_pos_neg_values($set){
		$yes='';
		$no='';
		for ($i=0; $i $no) return 'yes';
		else return 'no';	
	}
	
}//end decisiion tree class